نتایج جستجو برای: Stock price synchronicity

تعداد نتایج: 167885  

Journal: :Journal of Intelligent and Fuzzy Systems 2017
Gang Shi Zhiqiang Zhang Yuhong Sheng

Stock loan is different from the traditional loan, it needs to be collateralized by stock. Fairly valuing stock loan is very important for financial market participants. The main contribution of this paper is to give a valuing method of stock loan in uncertain environment. Under the assumption that the underlying stock price follows an uncertain mean-reverting stock model, the price formulas of...

Journal: :journal of industrial strategic management 2014
s. a. nabavi chashmi j. ghasemi chali

different areas of modern financial tools and processes activities contain the matters like innovations in financial tools engineering and risk management. derivatives and especially stock exchange option is part of this innovation. among all numerical procedures in calculating the value of derivatives and the risk sensitivity parameters of option, binomial models are widely used. in this stud...

Journal: :Operations Research 2016
Xin Chen Peng Hu Stephen Shum Yuhan Zhang

We analyze the joint inventory and pricing decisions of a firm when demand depends on not only the current selling price but also a memory-based reference price and customers are loss averse. The presence of reference price effect leads to a non-concave one-period expected revenue in price and reference price. We introduce a transformation technique that allows us to prove under some mild assum...

2012
Marko Miletić

The aim of this research is to analyze the connection between dividend announcement and stock price on Croatian capital market using event study methodology. Research period was the period from the year 2007 to the year 2009. Results have confirmed that dividend change has statistically significant value for investors. Dividend increase and dividend decrease resulted with statistically signific...

2015
Yu-Lei Wan Wen-Jie Xie Gao-Feng Gu Zhi-Qiang Jiang Wei Chen Xiong Xiong Wei Zhang Wei-Xing Zhou

Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders' short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock ...

1981
ROBERT J. SHILLER

A simple model that is commonly used to interpret movements in corporate common stock. price indexes asserts that real stock prices equal the present value of rationally expected or optimally forecasted future real dividends discounted by a constant real discount rate. This valuation model (or variations on it in which the real discount rate is not constant but fairly stable) is often used by e...

2016
S. Prasanna

The application of AI techniques for stock price prediction leads to voluminous growth of wealth of investors with the advent of technology. Several prediction and estimations are coming up for almost all sectors of the market. Particularly any kind of stock price prediction is not at all possible without excessive data manipulation which can be done effectively only thru data mining. The syste...

2007
Jesper Lund Pedersen

An optimal selling strategy for stock trading is presented in this paper. An investor with a long position in one stock decides to close the position before a given time. The investor continuously observes the stock price performance and has to determine the point in time to close out the position (selling strategy) so that the stock price is as close as possible to the maximum price. The proba...

2004
Jae Won

Recently, numerous investigations for stock price prediction and portfolio management using machine learning have been trying to develop efficient mechanical trading systems. But these systems have a limitation in that they are mainly based on the supervised leaming which is not so adequate for leaming problems with long-term goals and delayed rewards. This paper proposes a method of applying r...

2017
Wei Bao Jun Yue Yulei Rao

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock pr...

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